@inproceedings{4494cc08e55e462b9840e7e3fa3be63f,
title = "Query Expansion Based on User Requirements Clustering for Finding Feature Location",
abstract = "Feature Location is an approach of how to determine the code area based on high level software artifacts. Use Case Scenarios (UCS) are requirements documents in software artifacts that contain many words. A sentence in a UCS is sometimes described by a sentence in other UCS, so capture the relationship among UCS may be advantageous in finding feature locations. The research contribution is how to find feature locations better by making an expansion to query based on UCS clustering. The method was clustering the UCS using k-medoids clustering and index the source code using latent dirichlet allocation. The results was 56.8% for the best recall rate.",
keywords = "Clustering, Feature location, Latent Dirichlet Allocation, Use Case Scenario, research",
author = "Achmad Arwan and Siti Rochimah and Chastine Fatichah",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 6th International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2022 ; Conference date: 13-12-2022 Through 14-12-2022",
year = "2022",
doi = "10.1109/ICITISEE57756.2022.10057893",
language = "English",
series = "Proceeding - 6th International Conference on Information Technology, Information Systems and Electrical Engineering: Applying Data Sciences and Artificial Intelligence Technologies for Environmental Sustainability, ICITISEE 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "149--153",
booktitle = "Proceeding - 6th International Conference on Information Technology, Information Systems and Electrical Engineering",
address = "United States",
}